Intelligent construction method of fabricated building

Abstract

The invention relates to the technical field of fabricated buildings, and discloses an intelligent construction method of a fabricated building, comprising the following steps: S1, green building analysis: analyzing whether green building requirements are met; s2, collision simulation detection: simulating a collision condition between the components during hoisting; s3, a prefabricated part hoisting plan is made, wherein a hoisting progress plan is made; s4, making a prefabricated part production plan: making the prefabricated part production plan; s5, detecting the quality of the prefabricated part: detecting the quality index of the prefabricated part; s6, adjusting the external dimension deviation: adjusting the external dimension deviation; and S7, progress deviation adjustment, wherein deviation correction is conducted on the progress deviation. According to the invention, collision points are eliminated and the hoisting risk is reduced by simulating the collision condition which may occur during hoisting; a prefabricated part hoisting plan and a prefabricated part production plan are compiled; the continuous hoisting operation is met; and by adjusting the external dimension deviation and the progress deviation, it is guaranteed that hoisting operation is completed smoothly, and a qualified building is obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of prefabricated buildings, and in particular to an intelligent construction method for prefabricated buildings. Background Art

[0002] Prefabricated buildings refer to construction projects in which the building components of assembled houses are transported to the construction site for assembly through engineering manufacturing. Its characteristics are that the main components such as beams, columns, walls, and slabs used in the construction are all prefabricated, not cast at the construction site; and all kinds of components are assembled and connected at the construction site; intelligent construction refers to the use of information technology and intelligent equipment to digitally and intelligently manage and control the entire process of construction, realizing all-round digital management and automated control from design to construction; therefore, applying intelligent construction to prefabricated buildings can greatly improve construction efficiency, reduce labor costs, and improve building quality.

[0003] A Chinese patent discloses an intelligent construction method and construction system for prefabricated buildings (authorization announcement number CN109977450B). This patented technology can solve the problem of poor coordination, process errors and low efficiency in the operation of manually-led components. However, it cannot avoid collisions between different components during the construction process, and cannot control the production source of prefabricated components, resulting in unreasonable arrangement of component production and hoisting, and it is also impossible to correct the progress and size during the hoisting process. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent construction method for prefabricated buildings to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: An intelligent construction method for prefabricated buildings comprises the following steps: S1. Green building analysis: According to the design requirements, build various professional models according to the design drawings of the building, and form a 3D visualization model, which is then imported into the green building design evaluation software to simulate and calculate the green building requirements and analyze whether it meets the green building requirements. If it does, proceed to the next step. If not, modify the model until it meets the green building requirements; S2. Collision simulation test: simulate the collision of different components in the same professional model, the collision of components between different professional models, the dynamic collision of different lifting equipment during operation, and the static collision of prefabricated components and cast-in-place connection nodes; S3. Prefabricated component hoisting plan: According to the construction period and construction site requirements of the prefabricated building, the hoisting tasks are decomposed, the hoisting operations of each prefabricated component are simulated, the time parameters and logical relationships of the hoisting of each prefabricated component are determined, the hoisting schedule is formulated, and the best time for each prefabricated component to arrive at the construction site and the temporary stacking location of the prefabricated components are determined, so that each prefabricated component is related in space and time; S4. Prefabricated component production plan: Prepare the prefabricated component production plan according to the hoisting schedule, and organize the production of prefabricated components in batches in the factory according to the production plan. At the same time, set the production nodes of key tasks in the prefabricated components, track the quality and progress of the production links of the prefabricated components, and upload the real-time production status to the management platform; S5. Prefabricated component quality inspection: According to the design requirements of the prefabricated components, the quality indicators of the prefabricated components that have been produced are inspected. After passing the inspection, a wireless radio frequency tag is attached to each prefabricated component, and the tag information is uploaded to the management platform; S6. Adjustment of appearance dimension deviation: At each lifting node, the assembled building is scanned by 3D laser to obtain the point cloud data of the building, and the dimension deviation is compared with the 3D visualization model to analyze the dimension deviation. A deviation prediction model is established to predict the cumulative deviation and determine whether the assembled building meets the design requirements. At the same time, the real-time status is uploaded to the management platform. S7. Progress deviation adjustment: The prefabricated components that have been produced as planned and tested as qualified will be transported to the site for storage. According to the hoisting schedule, hoisting operations will be carried out at the construction site. At the same time, hoisting nodes for key tasks in the prefabricated components will be set up to track the progress of the hoisting links of the prefabricated components. The deviation between the actual progress of each hoisting node and the planned progress will be detected and analyzed. At the same time, the real-time status will be uploaded to the management platform, and corrective measures will be taken when the progress deviation exceeds the set value.

[0006] As a further solution of the present invention: in the step S1, the professional models in the three-dimensional visualization model include architectural models, structural models, plumbing models, electromechanical models, beam-column node models and construction site models, wherein architectural modeling includes the exterior design, interior layout and furniture placement of the building, and structural modeling includes the frame structure, floor slabs, walls, beams and columns of the building.

[0007] As a further solution of the present invention: in the step S3, the time parameters of the hoisting include the earliest start time, earliest completion time, latest start time and latest completion time of the hoisting of each prefabricated component; the logical relationship of the hoisting includes the preceding work, following work, parallel work and overlapping work of the hoisting of each prefabricated component.

[0008] As a further solution of the present invention: in the step S4, the key tasks in the prefabricated component production process include template production, steel skeleton, mesh and embedded parts installation, concrete pouring, maintenance and demoulding treatment.

[0009] As a further solution of the present invention: in the step S5, the quality indicators of the prefabricated components include the appearance size, surface quality, crack resistance, durability and bending resistance of the prefabricated components; the label information includes the name, number, product batch, appearance size and quality grade of the prefabricated components.

[0010] As a further solution of the present invention: in the step S5, the method for establishing the deviation prediction model is as follows: S51, comparing the point cloud data obtained by the three-dimensional laser scanning with the corresponding data in the original three-dimensional visualization model, and accumulating the hoisting deviation data of each key part to obtain cumulative deviation data; S52, by calculating the development gray number and the endogenous control gray number in the cumulative deviation data, and then performing cumulative subtraction, a deviation development trend model is obtained; S53. Then, by performing residual test, correlation test and posterior difference test on the deviation development trend model, the satisfaction and credibility of the model are judged to obtain the deviation prediction model.

[0011] Compared with the prior art, the present invention has the following beneficial effects: The present invention forms a three-dimensional visual model and judges until it meets the green building requirements; by simulating the collision that may occur during hoisting, the collision points are eliminated, the hoisting risks are reduced, and the smooth progress of the prefabricated construction is ensured; by compiling the prefabricated component hoisting plan and the prefabricated component production plan; it satisfies the continuous hoisting operation and reduces the occupation of the site and funds; by adjusting the appearance size deviation and the progress deviation, it is ensured that the hoisting operation is completed smoothly and a qualified building is obtained. DETAILED DESCRIPTION

[0012] In an embodiment of the present invention, an intelligent construction method for an assembled building includes the following steps: S1. Green building analysis: According to the design requirements, build various professional models according to the design drawings of the building, and form a 3D visualization model, which is then imported into the green building design evaluation software to simulate and calculate green building requirements, such as light source and lighting, energy consumption, natural lighting and ventilation, noise prevention and control, and indoor temperature and humidity, and analyze whether it meets the green building requirements. If so, proceed to the next step. If not, modify the model until it meets the green building requirements; S2. Collision simulation test: simulate the collision of different components in the same professional model, the collision of components between different professional models, the dynamic collision of different lifting equipment during operation, and the static collision of prefabricated components and cast-in-place connection nodes. If a collision point occurs, optimize the design and lifting plan to eliminate the collision point, thereby reducing the lifting risk, ensuring the smooth progress of prefabricated construction, and preventing interference between lifting operations; S3. Prefabricated component hoisting plan: According to the construction period and construction site requirements of the prefabricated building, the hoisting tasks are decomposed, the hoisting operations of each prefabricated component are simulated, the time parameters and logical relationships of the hoisting of each prefabricated component are determined, a hoisting schedule is formulated, and the best time for each prefabricated component to arrive at the construction site and the temporary stacking location of the prefabricated components are determined, so that each prefabricated component is related in space and time; thereby making the site tidy, meeting the requirements of continuous hoisting operations, and reducing site occupancy and capital occupation; S4. Prefabricated component production plan: Prepare a prefabricated component production plan based on the hoisting schedule, and organize the production of prefabricated components in batches in the factory according to the production plan, such as producing the prefabricated components that will be hoisted first and the prefabricated components that will be hoisted later, so as to reduce the capital and site occupation; at the same time, set the production nodes of key tasks in prefabricated components, and track the quality and progress of the production links of prefabricated components, such as tracking and supervising the production materials and processes in the production process, which can effectively ensure that qualified prefabricated components are produced within the specified time; and upload the real-time production status to the management platform, so that the management personnel can track and supervise the production process of prefabricated components through the management platform in the background, further reduce the production risk, and provide guarantee for the completion of subsequent hoisting operations on time; S5. Prefabricated component quality inspection: According to the design requirements of prefabricated components, the quality indicators of the prefabricated components that have been produced are inspected. After passing the inspection, a wireless radio frequency tag is attached to each prefabricated component, and the tag information is uploaded to the management platform. The staff can obtain the relevant information of the prefabricated components by scanning the tag on site, and the management personnel can also view the relevant information of the prefabricated components in the background; S6. Adjustment of appearance dimension deviation: At each lifting node, the assembled building is scanned by 3D laser to obtain the point cloud data of the building, such as the building's location, length, width, and height coordinate data, and the dimension deviation is compared with the 3D visualization model to analyze the dimension deviation. A deviation prediction model is established to predict the cumulative deviation and determine whether the assembled building meets the design requirements. The real-time status is uploaded to the management platform. S7. Progress deviation adjustment: The prefabricated components that are produced as planned and tested as qualified are transported to the site for storage. According to the hoisting schedule, hoisting operations are carried out at the construction site. At the same time, hoisting nodes for key tasks in prefabricated components are set up to track the progress of the hoisting links of prefabricated components. The deviation between the actual progress and the planned progress of each hoisting node is detected and analyzed. At the same time, the real-time status is uploaded to the management platform, and corrective measures are taken when the progress deviation exceeds the set value. If the actual hoisting progress is seriously behind schedule, overtime or two-shift work measures are taken to speed up the work, ensuring that the hoisting operation is completed smoothly and a qualified building is obtained.

[0013] Preferably, in the step S1, the professional models in the three-dimensional visualization model include architectural models, structural models, plumbing models, electromechanical models, beam-column node models and construction site models, wherein architectural modeling includes the exterior design, interior layout and furniture placement of the building, and the elements considered include the size, shape, material and style of the building; structural modeling includes the frame structure, floor slabs, walls, beams and columns of the building, and the factors considered include the load-bearing capacity, seismic resistance and stiffness of the building.

[0014] Preferably, in the step S3, the time parameters of the hoisting include the earliest start time, earliest completion time, latest start time and latest completion time of the hoisting of each prefabricated component; the logical relationship of the hoisting includes the preceding work, following work, parallel work and overlapping work of the hoisting of each prefabricated component.

[0015] Preferably, in the step S4, key tasks in the prefabricated component production process include formwork production, steel skeleton, mesh and embedded parts installation, concrete pouring, maintenance and demoulding treatment. By tracking the key tasks, the quality and progress of the prefabricated components can be effectively controlled.

[0016] Preferably, in the step S5, the quality indicators of the prefabricated components include the appearance size, surface quality, crack resistance, durability and bending resistance of the prefabricated components; the label information includes the name, number, product batch, appearance size and quality grade of the prefabricated components.

[0017] Preferably, in step S5, the method for establishing the deviation prediction model is as follows: S51, comparing the point cloud data obtained by the three-dimensional laser scanning with the corresponding data in the original three-dimensional visualization model, and accumulating the hoisting deviation data of each key part to obtain cumulative deviation data; S52, by calculating the development gray number and the endogenous control gray number in the cumulative deviation data, and then performing cumulative subtraction, a deviation development trend model is obtained; S53. Then, by performing residual test, correlation test and posterior difference test on the deviation development trend model, the satisfaction and credibility of the model are judged to obtain the deviation prediction model.

[0018] What is described above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent construction method for prefabricated buildings, characterized in that: The following steps are involved: S1. Green building analysis: According to the design requirements, build various professional models according to the design drawings of the building, and form a 3D visualization model, which is then imported into the green building design evaluation software to simulate and calculate the green building requirements and analyze whether it meets the green building requirements. If it does, proceed to the next step. If not, modify the model until it meets the green building requirements; S2. Collision simulation test: simulate the collision of different components in the same professional model, the collision of components between different professional models, the dynamic collision of different lifting equipment during operation, and the static collision of prefabricated components and cast-in-place connection nodes; S3. Prefabricated component hoisting plan: According to the construction period and construction site requirements of the prefabricated building, the hoisting tasks are decomposed, the hoisting operations of each prefabricated component are simulated, the time parameters and logical relationships of the hoisting of each prefabricated component are determined, the hoisting schedule is formulated, and the best time for each prefabricated component to arrive at the construction site and the temporary stacking location of the prefabricated components are determined, so that each prefabricated component is related in space and time; S4. Prefabricated component production plan: Prepare the prefabricated component production plan according to the hoisting schedule, and organize the production of prefabricated components in batches in the factory according to the production plan. At the same time, set the production nodes of key tasks in the prefabricated components, track the quality and progress of the production links of the prefabricated components, and upload the real-time production status to the management platform; S5. Prefabricated component quality inspection: According to the design requirements of the prefabricated components, the quality indicators of the prefabricated components that have been produced are inspected. After passing the inspection, a wireless radio frequency tag is attached to each prefabricated component, and the tag information is uploaded to the management platform; S6. Adjustment of appearance dimension deviation: At each lifting node, the assembled building is scanned by 3D laser to obtain the point cloud data of the building, and the dimension deviation is compared with the 3D visualization model to analyze the dimension deviation. A deviation prediction model is established to predict the cumulative deviation and determine whether the assembled building meets the design requirements. At the same time, the real-time status is uploaded to the management platform. S7. Progress deviation adjustment: The prefabricated components that have been produced as planned and tested as qualified will be transported to the site for storage. According to the hoisting schedule, hoisting operations will be carried out at the construction site. At the same time, hoisting nodes for key tasks in the prefabricated components will be set up to track the progress of the hoisting links of the prefabricated components. The deviation between the actual progress of each hoisting node and the planned progress will be detected and analyzed. At the same time, the real-time status will be uploaded to the management platform, and corrective measures will be taken when the progress deviation exceeds the set value.

2. The intelligent construction method of an assembled building according to claim 1, characterized in that: In the step S1, the professional models in the three-dimensional visualization model include architectural models, structural models, plumbing models, electromechanical models, beam-column node models and construction site models, among which the architectural modeling includes the exterior design, interior layout and furniture placement of the building, and the structural modeling includes the frame structure, floor slabs, walls, beams and columns of the building.

3. The intelligent construction method of an assembled building according to claim 1, characterized in that: In the step S3, the time parameters of the hoisting include the earliest start time, earliest completion time, latest start time and latest completion time of the hoisting of each prefabricated component; the logical relationship of the hoisting includes the preceding work, following work, parallel work and overlapping work of the hoisting of each prefabricated component.

4. The intelligent construction method of an assembled building according to claim 1, characterized in that: In the S4 step, the key tasks in the prefabricated component production process include formwork production, steel skeleton, mesh and embedded parts installation, concrete pouring, curing and demoulding.

5. The intelligent construction method of an assembled building according to claim 1, characterized in that: In the step S5, the quality indicators of the prefabricated components include the appearance size, surface quality, crack resistance, durability and bending resistance of the prefabricated components; the label information includes the name, number, product batch, appearance size and quality grade of the prefabricated components.

6. The intelligent construction method of an assembled building according to claim 1, characterized in that: In the step S5, the method for establishing the deviation prediction model is as follows: S51, comparing the point cloud data obtained by the three-dimensional laser scanning with the corresponding data in the original three-dimensional visualization model, and accumulating the hoisting deviation data of each key part to obtain cumulative deviation data; S52, by calculating the development gray number and the endogenous control gray number in the cumulative deviation data, and then performing cumulative subtraction, a deviation development trend model is obtained; S53. Then, by performing residual test, correlation test and posterior difference test on the deviation development trend model, the satisfaction and credibility of the model are judged to obtain the deviation prediction model.